Instructions to use stuartmesham/deberta-large_spell_5k_6_p3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stuartmesham/deberta-large_spell_5k_6_p3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="stuartmesham/deberta-large_spell_5k_6_p3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("stuartmesham/deberta-large_spell_5k_6_p3") model = AutoModelForTokenClassification.from_pretrained("stuartmesham/deberta-large_spell_5k_6_p3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from stuartmesham/deberta-large_spell_5k_6_p3: direct link, hf CLI and curl.
- Browser
- Download file 1.64 GB
-
https://huggingface.co/stuartmesham/deberta-large_spell_5k_6_p3/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://stuartmesham/deberta-large_spell_5k_6_p3/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/stuartmesham/deberta-large_spell_5k_6_p3/resolve/main/pytorch_model.bin
1.64 GB
- Xet hash:
- a1cfcfcd0a5f1a3284d440620911ce7d983e4720214261a60813b3070f60bd22
- Size of remote file:
- 1.64 GB
- SHA256:
- d57d16c5c9599087f39ecf45a060c702ea950bd46a693f0eb745d746a12dfb4f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.